Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

134 results for “Forecasting Model”
Set a search alert
Research ArticleOpen accessIn the abstractForecasting Gold Prices Using Multiple Linear Regression MethodZ. Ismail, A. Yahya, A. ShabriProblem statement: Forecasting is a function in management to assist decision making. It is also described as the process of estimation in unknown future situations. In a more general term it is commonly known as prediction which refers to estimation of time series or longitudinal type data. Gold is a precious yellow commodity once used as money. It was made … …American Journal of Applied Sciences, Vol. 6, Issue 8 · 31 Aug 2009 · 11,099 accessesView PDFCite
Research ArticleOpen accessIn the abstractElectricity Load Forecasting based on Framelet Neural Network TechniqueMohammed K. AbdLoad forecasting is very essential to the operation of electricity companies. It enhances the energy-efficient and reliable operation of a power system. This study shows Electricity Load Forecasting modeling based on Framelet Neural Network Technique (FNN) for Baghdad City. Framelet technique is implemented to the time series data, decomposing the data into number of Framelet coefficient signals. The decomposed signals … …American Journal of Applied Sciences, Vol. 6, Issue 5 · 31 May 2009 · 8,278 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Generalized Discrete-Time Long Memory Volatility Model for Financial Stock ExchangeChin Wen CheongWe proposed a simple way to combine a few long memory models in financial market volatility modeling using daily, range and high frequency data. This model was able to fit the return, range of daily return or realized volatility under a parametric heavy-tailed distribution. Model was flexible to include additional volatility information as the contemporaneous variables. Empirical results found that … …American Journal of Applied Sciences, Vol. 4, Issue 12 · 31 Dec 2007 · 6,874 accessesView PDFCite
Research ArticleOpen accessIn the abstractOn the Predictability of Risk Box Approach by Genetic Programming Method for Bankruptcy PredictionAlireza Bahiraie, Noor Akma bt Ibrahim, A. K.M. AzharProblem statement: Theoretical based data representation is an important tool for model selection and interpretations in bankruptcy analysis since the numerical representation are much less transparent. Some methodological problems concerning financial ratios such as non-proportionality, non-asymetricity, non-scalicity are solved in this study and we presented a complementary technique for empirical analysis of financial ratios and bankruptcy risk. Approach: This study … …American Journal of Applied Sciences, Vol. 6, Issue 9 · 30 Sep 2009 · 7,953 accessesView PDFCite
Research ArticleOpen accessIn the abstractLevel of Non-Matching Primary Transplant Cases According to Repeat Transplants Cases and a New Bivariate Poisson DistributionRamalingam ShanmugamIn their practice, healthcare administrators and professionals often wonder about the non-matching level organs in transplants for the sake of future forecasting. Currently, there is no appropriate methodology to analyze the pertinent transplant data and describe the patterns. The lack of a suitable methodology in the literature originates from an incorrect impression that the primary transplant cases and the repeat … …Current Research in Medicine, Vol. 8, Issue 1 · 10 Jul 2017 · 9,154 accessesView PDFCite
Research ArticleOpen accessIn the abstractOnline Forums Hotspot Prediction Based on Sentiment AnalysisK. Nirmala Devi, V. Murali BhaskarnProblem statement: Online forums hotspot prediction is one of the significant research areas in web mining, which can help people make proper decision in daily life. Online forums, news reports and blogs, are containing large volume of public opinion information. Rapid growth of network arouses much attention on public opinion, it is important to analyse the public opinion in time … …Journal of Computer Science, Vol. 8, Issue 8 · 11 Jul 2012 · 7,363 accessesView PDFCite
Research ArticleOpen accessIn the abstractCerebrovascular Accident Attack Classification Using Multilayer Feed Forward Artificial Neural Network with Back Propagation ErrorOlatubosun Olabode, Bola Titilayo OlabodeProblem statement: Most important problems of medical diagnosis. When there is a cerebrovascular accident attach the chances of a successful treatment depends essentially on the early diagnosis. In practice the part of medical errors while diagnosing a stroke type comes to 20-45% even for experienced doctors and the scope of methods of neurovisualization at stroke diagnosis are limited. Approach: In … …Journal of Computer Science, Vol. 8, Issue 1 · 26 Oct 2011 · 7,335 accessesView PDFCite
Research ArticleOpen accessIn the abstractVolatility in Malaysian Stock Market: An Empirical Study Using Fractionally Integrated ApproachChin Wen CheongThis study explores the fractionally integrated (FI) time series analysis in Malaysian stock market. Four proxies of latent volatility, namely the absolute return, squared return and range-based (Parkinson and Garman and Klass) volatilities are selected for the empirical studies. In addition, the well-known FI autoregressive conditional variance (ARCH) type model is also taken into account for comparison purposes. Our empirical … …American Journal of Applied Sciences, Vol. 5, Issue 6 · 30 Jun 2008 · 6,712 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Computable General Equilibrium Model of Southern Region in Taiwan: The Impact of the Tainan Science-Based Industrial ParkChun-Chu Liu, Chia-Yon ChenThe primary modeling tools used to analyze regional economic issues include econometric forecasting models, fixed price Input-Output (I-O) multi-sector models, Social Accounting Matrix (SAM) and Computable General Equilibrium (CGE) models. CGE models combine the advantages of econometric, I-O models and SAM strengthening the theoretical basis of the modeling effort and thus enabling more precise policy analysis. The current CGE literature … …American Journal of Applied Sciences, Vol. 1, Issue 3 · 30 Sep 2004 · 7,219 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian Models for Time Series with Covariates, Trend, Seasonality, Autoregression and OutliersPitsanu Tongkhow, Nantachai KantananthaBayesian methods furnish an attractive approach to time series data analysis. This article proposes the forecasting models that can detect trend, seasonality, auto regression and outliers in time series data related to some covariates. Cumulative Weibull distribution functions for trend, dummy variables for seasonality, binary selections for outliers and latent autoregression for autocorrelated time series data are used for the … …Journal of Computer Science, Vol. 9, Issue 3 · 16 Apr 2013 · 6,662 accessesView PDFCite